When a rotational X-ray device like a CT scanner generates X-ray projections of the heart during a rotation of the X-ray source, the resulting projections will capture the heart in different cardiac phases. Due to the associated movement of the heart, a tomographic reconstruction that simply uses all projections would yield a blurred cross-sectional image of the heart. It is therefore common to use for a reconstruction only projections that correspond (approximately) to the same cardiac phase, wherein the cardiac phase may for example be characterized by simultaneously recorded electrocardiographic signals. As was described in literature, this approach may for example be implemented based on a standard Algebraic Reconstruction Technique (ART) algorithm by the introduction of “cardiac weights” (cf. T. Nielsen, R. Manzke, R. Proksa, M. Grass: “Cardiac cone-beam CT volume reconstruction using ART”, to be published in Med. Phys., 2005; T. Nielsen, et al.: “Feasibility Study of Iterative Reconstruction for Helical Cardiac Cone-Beam CT”, scientific paper presented at RSNA 2004). Cardiac weights quantify with the help of electrocardiographic signals the similarity of a cardiac phase to a given observation phase that is of interest (for example the systolic phase or the diastolic phase).
To improve the speed of iterative reconstruction algorithms, it has further been proposed to divide all available projections randomly into subsets and to use in each iteration step all projections of a subset simultaneously for the calculation of an image update (resulting in the “Ordered Subsets” variants of the basic algorithms).